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carpal tunnel syndrome (cts) is the most common entrapment neuropathy. it accounts 90% of all entrapment neuropathies all over the world. ultrasound is a non-invasive, cost effective and available para-clinical method which could be applied for cts diagnosis. cross-sectional area of the median nerve at the level of the inlet is considered as a diagnostic criterion in cts cases. in this study, t...

This review provides the basic principle and rational for ROC analysis of rating and continuous diagnostic test results versus a gold standard. Derived indexes of accuracy, in particular area under the curve (AUC) has a meaningful interpretation for disease classification from healthy subjects. The methods of estimate of AUC and its testing in single diagnostic test and also comparative studies...

Ranking measures play an important role in model evaluation and selection. Using both synthetic and real-world data sets, we investigate how different types and levels of noise affect the area under the ROC curve (AUC), the area under the ROC convex hull, the scored AUC, the Kolmogorov-Smirnov statistic, and the H-measure. In our experiments, the AUC was, overall, the most robust among these me...

The objective of this manuscript is to find area under the plasma concentrationtime curve (AUC) for multiple doses of salbutamol sulphate sustained release tablets (Ventolin oral tablets SR 8 mg, GSK, Pakistan) in the group of 18 healthy adults by using computational mathematics techniques. Following the administration of 4 doses of Ventolin tablets 12 hourly to 24 healthy human subjects and bi...

Abbreviations: AE: Adverse Event; AUC: Area under Plasma Concentration–time Curve; AUCinf: Area under Plasma Concentration-time Curve from Time Zero Extrapolated to Infinite Time; AUClast: Area under Plasma Concentration–time Curve from Time Zero to the Time of the Last Quantifiable Concentration; BMI: Body Mass Index; CI: Confidence Interval; Cmax: Maximum Plasma Concentration; CRU: Clinical R...

The Area Under the ROC Curve (AUC) has been recognised as a very robust measure for classification evaluation. Recent efforts have focussed on modifying existing algorithms to improve their AUC or even to use AUC as a search criterion [6]. In this paper, we suggest the possibility that we could improve the AUC of existing models and techniques, without changing the techniques or retraining the ...

The accuracy of a diagnostic test is typically characterised using the receiver operating characteristic (ROC) curve. Summarising indexes such as the area under the ROC curve (AUC) are used to compare different tests as well as to measure the difference between two populations. Often additional information is available on some of the covariates which are known to influence the accuracy of such ...